Senior Data Engineer
About The Position
Trackforce is seeking a highly skilled and motivated Senior Data Engineer to join our Data team. In this role, you will be responsible for designing, building, and maintaining the data infrastructure that powers our SaaS platform, enabling clients across the globe to manage their security workforces with speed, accuracy, and insight. You'll design and ship the pipelines and data models that move multi-tenant data from our platform into a modern, query-ready foundation. And you'll help shape the technical direction alongside the engineering manager and the team as we define the strategy. This is a zero-to-one role for someone who wants to build the foundation, not inherit it. This is a high-impact, technically deep role for an engineer who is passionate about scalable data systems, thrives in a collaborative environment, and is eager to help shape the data foundation of a growing global SaaS company.
Requirements
- Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related field (or equivalent hands-on experience).
- 7+ years in data engineering, with strong SQL and relational data modeling on large datasets.
- Proven experience designing and operating ETL/ELT pipelines into a data warehouse or data lake/lakehouse.
- Hands-on with AWS data services (e.g., S3, Glue, Athena; DMS or similar CDC tooling)
- Experience with distributed data processing (e.g., Spark/PySpark) and modern lakehouse table formats (e.g., Apache Iceberg, Delta), or a strong track record that transfers.
- Comfortable with streaming/queue-based ingestion (e.g., Kinesis, SQS, Kafka) and building for scale and failure.
- Solid grounding in data governance, quality, and compliance, ideally for multi-tenant SaaS data.
- Proficiency in pipeline automation.
- Clear communicator who ships pragmatically in ambiguity.
Nice To Haves
- dbt or similar transformation frameworks
- experience exposing client-facing data via APIs or governed data sharing
- SaaS or workforce-management/physical-security domain exposure
- familiarity with AI/ML data infrastructure patterns
Responsibilities
- Design, build, and operate scalable ETL/ELT pipelines that ingest, transform, and load multi-tenant data into a data warehouse/lakehouse.
- Build for change data capture (CDC) and high-volume, near-real-time ingestion; tune pipelines for reliability, performance, and cost.
- Help design the data models and lakehouse schema that make client-facing data accurate, performant, and secure to expose per tenant.
- Contribute to the API-as-product effort — data access patterns, versioning, and documentation that clients depend on.
- Establish data quality monitoring, alerting, and observability across core data domains.
- Implement multi-tenant data isolation and governance practices appropriate for enterprise, compliance-sensitive clients.
- Act as a go-to for investigating and resolving data integrity and availability issues.
- Partner across Product, Engineering, and DevOps to turn requirements into pragmatic data solutions.
- Share knowledge and mentor teammates as the team grows; help set a high bar for engineering quality.
- Use AI-assisted development tools in your own workflow (pipeline code, query optimization, documentation) and share what works.
- Build with an eye toward a data foundation that can later power analytics and AI/agent-based capabilities.
Benefits
- Hybrid and flexible work model
- Three weeks of vacation starting in your first year
- Paid sick days & family obligation days
- Comprehensive health & dental coverage from Day 1
- 24/7 telemedicine access
- Mental health & wellness support
- Life insurance, AD&D, long term‑ disability & critical illness coverage
- RRSP & DPSP with employer matching
- Employee referral bonus
- Paid volunteer day & recognition programs
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What This Job Offers
Job Type
Full-time
Career Level
Senior
